Laurence McLeanCentre for Research on the Epidemiology of Disasters – CREDUniversité Catholique de Louvain, Brussels, [email protected] www.cred.be
First Technical Workshop on Standards for Hazard Monitoring, Data, Metadata and Analysis to Support Risk Assessment
10- 14 June 2013
WMO, Geneva
State of Play Strong need for data: • Disaster events increasing
in magnitude & frequency
• Continuous need for disaster data collection
• Important tool for a variety of institutions and organisations
Problems:
• Lack of international consensus on best practice in collecting data
• Variability in definitions, terminology, sources, etc.
OVERVIEW OF EXISTING DATABASES• Global scale: 3 EM-DAT/CRED, NATCAT/MünichRe,
SIGMA/SwissRe.
(+/-50)
• Events Databases (i.e. DFO/Floods; USGS)
• National and sub-national databases
EM-DAT/CRED• Importance of measuring human impacts
• Emergency Events Database, created 1988, maintained by CRED, Université Catholique de Louvain, Brussels
• Project funded by OFDA/USAID, USA • Objective: Provide evidence-base to humanitarian and development actors at
national and international levels • Publicly available (www.emdat.be)
Total occurrence of natural disasters from 1950 to 2012*
Source: CRED
Total number affected by natural disasters from 1900 to 2012.
1%
33%
3%
51%
13%
Biological
Climatological
Geophysical
Hydrological
Meteorological
Source: CRED
EM-DAT DISASTER DEFINITION
“A situation or event which overwhelms local capacity, necessitating a request to a national or
international level for external assistance; an unforeseen and often sudden event that causes
great damage, destruction and human suffering”
EM-DAT Criteria• 10 or more people reported killed
and/or
• 100 or more people reported affected
and/or
• Call for international assistance /state of emergency is declared
Sources of informationMulti source policy, comprising of UN agencies, non-governmental organizations, insurance companies, research institutes and press agencies. Priority is given to data from:
1) UN agencies 2) OFDA 3) Governments 4) International Federation (IFRC)5) Insurance/reinsurance companies6) Research Institutions7) Press
Classification of Natural Disasters*• Biological disasters : Insect infestations, epidemics and animal attacks;• Geophysical disasters : Earthquakes and tsunamis, volcanic eruptions, dry
mass movements (avalanches, landslides, rockfalls and subsidences of geophysical origin)
• Climatological disasters : Droughts (with associated food insecurities), extreme temperatures and wildfires;
• Hydrological disasters : Floods (including waves and surges), wet mass movements (avalanches, landslides, rockfalls and subsidences of hydrological origin);
• Meteorological disasters : Storms (divided into 9 sub-categories).
*BELOW R., WIRTZ A., GUHA-SAPIR D. (2009). Disaster Category Classification and Peril Terminology for Operational Purposes, CRED: Brussels; MunichRe: Münich
EM-DAT/INDICATORS*• Human indicators
– Deaths : Persons confirmed as dead and persons missing and presumed dead (official figures when available)
– Affected: People requiring immediate assistance during a period of emergency; it can also include displaced or evacuated people
– Injured: People suffering from physical injuries, trauma or an illness requiring medical treatment as a direct result of a disaster.
– Homeless: People needing immediate assistance for shelter.– Total affected: Sum of injured, homeless, and affected.
* CRED currently working on the harmonization of human and economic indicators (in collaboration with MünichRe ,SwissRe, UNDP, …)
EM-DAT/INDICATORS*• Economic impact
– Direct economic losses: Given by sector (when available) and expressed in US$ (at the time the disaster happens)
– Insured losses and reconstruction cost
* CRED currently working on the harmonization of human and economic indicators (in collaboration with MünichRe ,SwissRe, UNDP, …)
EMDAT CREDibility• Over 20 years experience
in data collection and management
• Transparency and automatisation (data entry and ouput)
• Consistent methodology, Rules and definition
• Validation methods and tools
The result: data is comparable over
time and space
WEAKNESSES OF EM-DAT• Global database
• Limited potential for analysis of disaster occurrence and impact on smaller, intra-country spatial scale.
• Public usage of EM-DAT may lead to inappropriate use
What is the challenge? • Lack of clear standardised collection methodologies
and definitions. • Inconsistencies, data gaps, poor inter-operability etc.
Confusion in evaluating disaster situations and causes
obstacles for disaster prevention and preparedness.
Quality of Disaster Databases can only be as good
as the reporting systems which feed them
Successful and sustainable databases – what is the criteria?
• Clear and limited scope (i.e. variables)
• Best environment (academic vs gov. administration)
• Scientifically sound methodologies and definitions
Next steps forward for EM-DAT disaster database
• 85% of natural disaster related deaths occur in Asian
• In 2010, CRED undertook a study of disaster collection efforts in six Asian countries http://www.cred.be/sites/default/files/WP272.pdf
• Aim of to strengthen national structures
Decentralisation of disaster data collection…why? • Local sources are better positioned to reflect the local picture
• Downscaling to national and sub national level can lead to improved data quality
• Potential for project sustainability as partner institutions take ownership and responsibility
• Overall aim: To set up a concentric system of disaster impact data collection –
interoperable between sub-national, national, regional and global levels – using a harmonised set definitions and methods.
• Through this CRED hopes to develop NEM-DAT for Asia.
Inter-operability system
Sub-National
National
Regional
Global
Methodological Issues What has improved?
- Information systems in the last 30 years- Availability of statistical data
Better Quality of Data
What is still lacking?
- No systematic and standardized data collection for historical data
- Standards and definitions
Key Problems Lack of standardized collection methodologies and definitions, ambiguities exist regarding:
1. Intent behind data reporting:i.e. Data not gathered for statistical purposes
2. Dates reportedi.e. Long-term disaster (Drought/Famine)
3. Loss definition of human impact i.e. Definition of affected is open to different interpretation
4. Evaluation methods of damagesi.e. Poor reporting, no internationaly accepted methods
5. Geographical locationi.e. Change in national boundaries
Challenges
Improving the completeness of information (disaggregated data)
– Limitations : • Comparability and inter-operability• Data collection initiatives project-based (lack of long-term
perspective)• Lack of comprehensive policy among organizations
WHAT ARE THE NEEDS?
• Adequate database structures• Standardized methodology and operational approaches• Interoperability• Sustainability
STRENGHTS OF EM-DAT• Unique free accessible database
• Acts as a reference point for global analysis of disaster occurrence and impact
• Unique basis for policy paper on disaster reduction and risks
• International recognition and CREDibility
• Capacity to provide methods and guidelines
